This disclosure relates generally to tagging transactions, and more particularly to methods and an apparatus for fuzzy tagging.
Tags are used to categorize transactions in various models. Making a model includes analysis of historical data to determine variables indicative of fraudulent or non fraudulent transactions. When looking at historical data, the transaction is known to be either fraudulent or non fraudulent. Tags indicate whether the transaction was fraudulent. For example, a tag value of “1” is used to indicate that the transaction is fraudulent and a tag value of “0” in the same filed is used to indicate a non fraudulent transaction. After a model is produced, it is used to predict whether real time or substantially real time transactions are fraudulent or non fraudulent. Generally, when predicting the category of the transaction, the models tend to place questionable transactions in the fraudulent category. In other words, it is safer and more economically judicious to predict a transaction will be fraudulent rather than non fraudulent. Currently, the tags used lack any granularity.